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Intro
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Classroom Contents
Deciphering Doctor's Handwriting with Deep Learning
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- 1 Intro
- 2 Business goal
- 3 Case 2: the Doctor's Consultation Certificate
- 4 Case 1: the Death Certificate
- 5 Data pipeline
- 6 Mining
- 7 Original image
- 8 Line segmentation
- 9 Baseline
- 10 Training set definition
- 11 Data quality
- 12 Data partitioning: split into text lines
- 13 Deep-Learning Model
- 14 Ensemble modelling
- 15 Model Training Performance
- 16 Model accuracy
- 17 Prediction confidence levels
- 18 Confidence plot
- 19 Examples target population
- 20 Examples false positives
- 21 Statistics false positives
- 22 Examples low confidence
- 23 Example: type A
- 24 Language detection
- 25 Certificate type detection
- 26 Preprocessing
- 27 Training data
- 28 Nomenclature code
- 29 Date of Consultation
- 30 Comparison OCR - Neural Network
- 31 The Grid (5)
- 32 Some grid examples
- 33 Approach
- 34 Examples: 2 lines
- 35 Training on histogram features
- 36 Results number of lines prediction
- 37 Reading the lines
- 38 Examples: high confidence false predictions
- 39 Grid summary
- 40 Second challenge: different patterns
- 41 Fourth challenge: rotations
- 42 Fifth challenge: superposition and readability
- 43 Step 1: find the stamp
- 44 Intersection over Union
- 45 Summary stamp reading
- 46 Application Integration
- 47 Conclusion
